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Multiple Social Networks, Data Models and Measures for

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Encyclopedia of Social Network Analysis and Mining
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Synonyms

Heterogeneous; Multidimensional; Multilayer; Multilayered; Multimodal; Multiplex networks; Multislice; Multitype

Glossary

A Social Network (SN):

is a set of social relationships between actors, where actors represent individuals, groups of individuals, or larger organizations. A social network can also contain nonrelational information, such as data about the individuals.

A Social Network Site (SNS):

is a Web 2.0 site where users can create user profiles and interact with other users, for example sharing messages.

An Online Social Network (OSN):

contains information collected from a SNS or from other online services about online interactions.

Definition

Multiple Social Network Analysis is a discipline defining models, measures, methodologies, and algorithms to study multiple social networks together as a single social system. It is particularly valuable when the networks are interconnected, e.g., the same actors are present in more than one network.

Introduction

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References

  • Afsarmanesh N, Magnani M (2016) Finding overlapping communities in multiplex networks. http://arxiv.org/abs/1602.03746

  • Battiston F, Nicosia V, Latora V (2014) Structural measures for multiplex networks. Phys Rev E 89(3):032804. https://doi.org/10.1103/PhysRevE.89.032804

    Article  Google Scholar 

  • Berlingerio M, Coscia M, Giannotti F (2011a) Finding and characterizing communities in multidimensional networks. In: International conference on advances in social networks analysis and mining (ASONAM), IEEE Computer Society Washington, DC, USA, pp. 490–494

    Google Scholar 

  • Berlingerio M, Coscia M, Giannotti F, Monreale A, Pedreschi D (2011b) Foundations of multidimensional network analysis. In: 2011 International conference on advances in social networks analysis and mining, IEEE Computer Society Washington, DC, USA, pp. 485–489. https://doi.org/10.1109/ASONAM.2011.103

  • Berlingerio M, Pinelli F, Calabrese F (2013) ABACUS: frequent pAttern mining-BAsed community discovery in mUltidimensional networkS. Data Min Knowl Disc 27(3):294–320

    Article  MathSciNet  MATH  Google Scholar 

  • Boyd D (2008) Taken out of context: American teen sociality in networked publics. PhD thesis, University of California-Berkeley, School of Information

    Google Scholar 

  • Boyd D (2010) Privacy and publicity in the context of big data. WWW. Raleigh, North Carolina, April 29. http://www.danah.org/papers/talks/2010/WWW2010.html

  • Bródka P, Stawiak P, Kazienko P (2011) Shortest path discovery in the multi-layered social network. In: 2011 International conference on advances in social networks analysis and mining, IEEE Computer Society Washington, DC, USA, pp. 497–501. https://doi.org/10.1109/ASONAM.2011.67

  • Bródka P, Kazienko P, Musial K, Skibicki K (2012) Analysis of neighbourhoods in multi-layered dynamic social networks. Int J Comp Intel Sys 5(3):582–596

    Article  Google Scholar 

  • Buldyrev SV, Parshani R, Paul G, Stanley HE, Havlin S (2010) Catastrophic cascade of failures in interdependent networks. Nature 464(7291):1025–1028. https://doi.org/10.1038/nature08932

    Article  Google Scholar 

  • Cai D, Shao Z, He X, Yan X, Han J (2005a) Community mining from multi-relational networks. PKDD 3721:445–452. https://doi.org/10.1007/11564126 44

    Article  Google Scholar 

  • Cai D, Shao Z, He X, Yan X, Han J (2005b) Mining hidden community in heterogeneous social networks. In: International workshop on link discovery (LinkKDD), ACM Press, pp. 58–65. https://doi.org/10.1145/1134271.1134280

  • Celli F, Di Lascio FML, Magnani M, Pacelli B, Rossi L (2010) Social network data and practices: the case of friendfeed. In: International conference on social computing, behavioral modeling and prediction, Lecture notes in computer science. Springer, Berlin/Heidelberg

    Google Scholar 

  • Cheng X, Dale C, Liu J (2008) Statistics and social network of YouTube videos. In: 2008 16th International workshop on quality of service, IEEE Press Piscataway, NJ, USA, pp. 229–238. https://doi.org/10.1109/IWQOS.2008.32

  • Contractor N (2009) The emergence of multidimensional networks. J Comput-Mediat Commun 14(3):743–747. https://doi.org/10.1111/j.1083-6101.2009.01465.x

    Article  Google Scholar 

  • Cozzo E, Kivelä M, De Domenico M, Solé A, Arenas A, Gómez S, Porter MA, Moreno Y (2015) Structure of triadic relations in multiplex networks. New J Phys 17, 073029

    Google Scholar 

  • De Domenico M, Nicosia V, Arenas A, Latora V (2015) Structural reducibility of multilayer networks. Nat Commun, 6:6864

    Google Scholar 

  • De Domenico M, Porter MA, Arenas A (2015) MuxViz: a tool for multilayer analysis and visualization of networks. J Complex Netw, 3(2): 159–176

    Google Scholar 

  • Dickison ME, Magnani M, Rossi L (2016) Multilayer social networks. Cambridge University Press

    Google Scholar 

  • Fatemi Z, Salehi M, Magnani M (2016) A simple multiforce layout for multiplex networks. http://arxiv.org/abs/1607.03914

  • Fortunato S (2010) Community detection in graphs. Phys Rep 486(3–5):75–174. https://doi.org/10.1016/j.physrep.2009.11.002

    Article  MathSciNet  Google Scholar 

  • Huang L, Liu J (2010) Characterizing multiplex social dynamics with autonomy oriented computing. In: Life system modeling and intelligent computing, Lecture Notes in Computer Science, vol 6329. Springer, Berlin, Heidelberg, pp 277–287

    Google Scholar 

  • Huberman BA, Romero DM, Wu F (2009) Social network that matter: twitter under the microscope. First Monday 14(1)

    Google Scholar 

  • Iacobucci D, Wasserman S (1990) Social networks with two sets of actors. Psychometrika 55(4):707–720

    Article  Google Scholar 

  • Kazienko P, Bródka P, Musial K, Gaworecki J (2010a) Multi-layered social network creation based on bibliographic data. In: Elmagarmid AK, Agrawal D (eds) SocialCom/PASSAT, IEEE Computer Society, pp 407–412

    Google Scholar 

  • Kazienko P, Bródka P, Musial K, Gaworecki J (2010b) Multi-layered social network creation based on bibliographic data. In: 2010 I.E. second international conference on social computing, IEEE, pp. 407–412. https://doi.org/10.1109/SocialCom.2010.65

  • Kivelä M, Arenas A, Barthelemy M, Gleeson JP, Moreno Y, Porter MA (2014) Multilayer networks. J Commun Netw 2(3):203–271. https://doi.org/10.1093/comnet/cnu016

    Article  Google Scholar 

  • Lazega E, Pattison PE (1999) Multiplexity, generalized exchange and cooperation in organizations: a case study. Soc Networks 21(1):67–90

    Article  Google Scholar 

  • Lazega E, Jourda MT, Mounier L, Stofer R (2008) Catching up with big fish in the big pond? Multilevel network analysis through linked design. Soc Networks 30(2):159–176

    Article  Google Scholar 

  • Leskovec J, Huttenlocher D, Kleinberg J (2010) Predicting positive and negative links in online social networks. In: Proceedings of the 19th international conference on World wide web, ACM, New York, WWW’10, pp. 641–650. https://doi.org/10.1145/1772690.1772756.

  • Magnani M, Rossi L (2011a) The ML-model for multilayer network analysis. In: IEEE international conference on advances in social network analysis and mining, IEEE Computer Society, Los Alamitos.

    Google Scholar 

  • Magnani M, Rossi L (2011b) The ML-model for multi-layer social networks. In: International conference on social network analysis and mining (ASONAM), IEEE Computer Society Washington, DC, USA, pp. 5–12.

    Google Scholar 

  • Magnani M, Rossi L (2013a) Formation of multiple networks. In: Social computing, behavioral-cultural modeling and prediction. Springer, Berlin Heidelberg, pp 257–264

    Chapter  Google Scholar 

  • Magnani M, Rossi L (2013b) Pareto distance for multi-layer network analysis. In: Greenberg AM, Kennedy WG, Bos ND (eds) Social computing, behavioral-cultural modeling and prediction, Lecture notes in computer science, vol 7812. Springer, Berlin. https://doi.org/10.1007/978-3-642-37210-0

    Chapter  Google Scholar 

  • Minor MJ (1983) New directions in multiplexity analysis. In: Burt RS, Minor MJ (eds) Applied network analysis. Sage, pp 223–244

    Google Scholar 

  • Moreno JL, Jennings HH (1934) Who shall survive?: a new approach to the problem of human interrelations. Nervous and Mental Disease Publishing Co., Washington, DC

    Book  Google Scholar 

  • Mucha PJ, Richardson T, Macon K, Porter MA, Onnela JP (2010) Community structure in time-dependent, multiscale, and multiplex networks. Science 328(5980):876–878. https://doi.org/10.1126/science.1184819

    Article  MathSciNet  MATH  Google Scholar 

  • Pepe A, Wolff S, Godtsenhoven KV (2011) One, none and one hundred thousand profiles: reimagining the pirandellian identity dilemma in the era of online social networks, arXiv:1109.3428

    Google Scholar 

  • Rainie L, Wellman B (2012) Networked: the new social operating system. MIT Press, Cambridge

    Google Scholar 

  • Rossi L, Magnani M (2015) Towards effective visual analytics on multiplex and multilayer networks. Chaos, Solitons, Fractals 72:68–76

    Article  MathSciNet  Google Scholar 

  • Stefanone M, Kwon K, Lackaff D (2011) The value of online friends: networked resources via social network sites. First Monday 16(2)

    Google Scholar 

  • Sun Y, Han J, Zhao P, Yin Z, Cheng H, Wu T (2009) RankClus. In: Proceedings of the 12th international conference on extending database technology advances in database technology – EDBT’09, ACM Press, New York, p. 565. https://doi.org/10.1145/1516360.1516426

  • Sun Y, Han J, Aggarwal CC, Chawla NV (2012) When will it happen? In: Proceedings of the fifth ACM international conference on Web search and data mining – WSDM’12, ACM Press, New York, p. 663. https://doi.org/10.1145/2124295.2124373

  • Szell M, Lambiotte R, Thurner S (2010) Multirelational organization of large-scale social networks in an online world. PNAS 107(31):13636–13641

    Article  Google Scholar 

  • Tang L, Liu H (2009) Relational learning via latent social dimensions. In: Proceedings of the 15th ACM SIGKDD international conference on knowledge discovery and data mining, ACM Press, New York, KDD’09, pp. 817–826. https://doi.org/10.1145/1557019.1557109

  • Turkle S (1995) Life on the screen: identity in the age of the internet. Simon & Schuster, New York

    Google Scholar 

  • Verbrugge LM (1979) Multiplexity in adult friendships. Soc Forces 57(4):1286–1309. https://doi.org/10.1093/sf/57.4.1286

    Article  Google Scholar 

  • Yin X, Han J, Yu PS (2006) LinkClus: efficient clustering via heterogeneous semantic links. In: Proceedings of the 32nd international conference on very large data bases, VLDB Endowment, VLDB’06 Endowment, pp. 427–438

    Google Scholar 

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Correspondence to Matteo Magnani .

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Magnani, M., Rossi, L. (2018). Multiple Social Networks, Data Models and Measures for. In: Alhajj, R., Rokne, J. (eds) Encyclopedia of Social Network Analysis and Mining. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-7131-2_33

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